Improve quality and manufacturing through data-driven decision-making by governing quality return rates forecast through in-house developed algorithms, owning the strategy and development of scalable data tools, prototyping GenAI and advanced dashboards, and leading analytics to solve critical business problems.
Requirements
- coding (e.g., Python, R, SQL)
- querying databases
- statistical analysis
- Experience using ETL tools.
- Experience conducting root cause analysis.
Responsibilities
- Use custom data infrastructure or existing data models as appropriate.
- Design and evaluate models to mathematically express and solve defined problems with limited precedent.
- Develop specialized tools for root cause analysis, station diagnostics, and statistical process control (SPC) to enable continuous improvement.
- Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python).
- Format, re-structure, or validate data to ensure quality.
- Analyze telemetry data and customer sentiment to quantify its impact on quality and inform design improvements.
Other
- Master's degree in statistics, data science, mathematics, physics, economics, operations research, engineering, a related quantitative field, or equivalent practical experience.
- 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.
- Experience supporting manufacturing, supply chain, or quality analytics.
- Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions.
- Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
